---

Overview

Translate-15L is a lightweight multilingual translation model trained on OPUS100.

Rather than maximizing parameter count, the model focuses on providing practical multilingual translation with fast inference and a compact footprint.

It supports translation between English and 14 additional languages in both directions.

---

Quick Start

from transformers import AutoTokenizer, T5ForConditionalGeneration

model = T5ForConditionalGeneration.from_pretrained(
    "WhirlwindAI/Translate-15L"
)

tokenizer = AutoTokenizer.from_pretrained(
    "WhirlwindAI/Translate-15L"
)

text = "Hello, how are you?"

prompt = f"translate en to fr: {text}"

inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(
    **inputs,
    max_new_tokens=50,
    num_beams=4
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

---

Supported Languages

---

Performance

BLEU Evaluation

Language Overview

---

Highlights

---

Speed

⚡ ~8,151 Tokens / Second

Fast enough for lightweight multilingual applications while remaining compact.

See speed.txt for the complete benchmark.

---

Examples

---

Notes

• English ↔ 14 Languages
• Optimized for compact deployment
• Trained on OPUS100
• Best performance on high-resource European languages
• Performance on low-resource languages remains limited

---

WhirlwindAI

Efficient AI • Practical Research • Open Models